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Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Amit Misra , Kevin White , Simone Fobi Nsutezo , William Straka , Juan Lavista

Due to its cloud-penetrating capability and independence from solar illumination, satellite Synthetic Aperture Radar (SAR) is the preferred data source for large-scale flood mapping, providing global coverage and including various land…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Jie Zhao , Zhitong Xiong , Xiao Xiang Zhu

Satellite remote sensing presents a cost-effective solution for synoptic flood monitoring, and satellite-derived flood maps provide a computationally efficient alternative to numerical flood inundation models traditionally used. While…

Geophysics · Physics 2022-09-05 Antara Dasgupta , Lasse Hybbeneth , Björn Waske

Accurate flood detection from visual data is a critical step toward improving disaster response and risk assessment, yet datasets for flood segmentation remain scarce due to the challenges of collecting and annotating large-scale imagery.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Georgios Simantiris , Konstantinos Bacharidis , Apostolos Papanikolaou , Petros Giannakakis , Costas Panagiotakis

Flooding is one of the most destructive natural hazards worldwide, posing serious risks to ecosystems, infrastructure, and human livelihoods. This study combines Synthetic Aperture Radar (SAR) imagery with environmental and hydrological…

Machine Learning · Computer Science 2025-12-29 Edwin Oluoch Awino , Denis Machanda

The frequency of extreme flood events is increasing throughout the world. Daily, high-resolution (30m) Flood Inundation Maps (FIM) observed from space play a key role in informing mitigation and preparedness efforts to counter these extreme…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Akshay Aravamudan , Zimeena Rasheed , Xi Zhang , Kira E. Scarpignato , Efthymios I. Nikolopoulos , Witold F. Krajewski , Georgios C. Anagnostopoulos

This study introduces a novel dataset for segmenting flooded areas in satellite images. After reviewing 77 existing benchmarks utilizing satellite imagery, we identified a shortage of suitable datasets for this specific task. To fill this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Youngsun Jang , Dongyoun Kim , Chulwoo Pack , Kwanghee Won

Driven by rapid climate change, the frequency and intensity of flood events are increasing. Electro-Optical (EO) satellite imagery is commonly utilized for rapid response. However, its utilities in flood situations are hampered by issues…

Computer Vision and Pattern Recognition · Computer Science 2023-07-17 Minseok Seo , Youngtack Oh , Doyi Kim , Dongmin Kang , Yeji Choi

Pakistan experienced an unusually severe flood season between June and December 2025, with cascading impacts on population, infrastructure, and agriculture. Existing operational flood products (e.g., UNOSAT) provide valuable episode-level…

Atmospheric and Oceanic Physics · Physics 2026-05-13 Usman Nazir , Disha Gomathinayagam , Muhammad Kamran , Sara Khalid

A recent report from the World Meteorological Organization (WMO) highlights that water-related disasters have caused the highest human losses among natural disasters over the past 50 years, with over 91\% of deaths occurring in low-income…

Machine Learning · Computer Science 2025-01-14 Ting-Yu Dai , Hayato Ushijima-Mwesigwa

Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information. Instruments and sensors useful for flood detection are only…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Peri Akiva , Matthew Purri , Kristin Dana , Beth Tellman , Tyler Anderson

Earth observation technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to monitor ever-growing urban environments continuously. Notably, in the case of large-scale disasters (e.g., tsunamis and…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Bruno Adriano , Naoto Yokoya , Junshi Xia , Hiroyuki Miura , Wen Liu , Masashi Matsuoka , Shunichi Koshimura

Floods are increasingly frequent natural disasters causing extensive human and economic damage, highlighting the critical need for rapid and accurate flood inundation mapping. While remote sensing technologies have advanced flood monitoring…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Tomohiro Tanaka , Narumasa Tsutsumida

Flooding is the most devastating phenomenon occurring globally, particularly in mountainous regions, risk dramatically increases due to complex terrains and extreme climate changes. These situations are damaging livelihoods, agriculture,…

Artificial Intelligence · Computer Science 2025-05-27 Haleema Bibi , Sadia Saleem , Zakia Jalil , Muhammad Nasir , Tahani Alsubait

Climate change has increased the severity and frequency of weather disasters all around the world. Flood inundation mapping based on earth observation data can help in this context, by providing cheap and accurate maps depicting the area…

Machine Learning · Computer Science 2023-03-02 Kevin Iselborn , Marco Stricker , Takashi Miyamoto , Marlon Nuske , Andreas Dengel

A reliable yet inexpensive tool for the estimation of flood water spread is conducive for efficient disaster management. The application of optical and SAR imagery in tandem provides a means of extended availability and enhanced reliability…

Computer Vision and Pattern Recognition · Computer Science 2023-06-12 Usman Nazir , Muhammad Ahmad Waseem , Falak Sher Khan , Rabia Saeed , Syed Muhammad Hasan , Momin Uppal , Zubair Khalid

Vision is essential for human navigation. The World Health Organization (WHO) estimates that 43.3 million people were blind in 2020, and this number is projected to reach 61 million by 2050. Modern scene understanding models could empower…

Surface water dynamics play a critical role in Earth's climate system, influencing ecosystems, agriculture, disaster resilience, and sustainable development. Yet monitoring rivers and surface water at fine spatial and temporal scales…

Urban flooding affects lives and infrastructure worldwide. Mapping inundation in complex urban environments from satellite imagery remains challenging due to limited spatial resolution, infrequent acquisitions, and cloud cover. We present…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Rohit Mukherjee , Hannah K. Friedrich , Beth Tellman , Ariful Islam , Zhijie Zhang , Jonathan Giezendanner , Upmanu Lall , Venkataraman Lakshmi

The detection of flooded areas using high-resolution synthetic aperture radar (SAR) imagery is a critical task with applications in crisis and disaster management, as well as environmental resource planning. However, the complex nature of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Tamer Saleh , Xingxing Weng , Shimaa Holail , Chen Hao , Gui-Song Xia
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